Sr. AI Solutions Architect
Why Open: AI Implementation
Boston, MA
Duration: 6 months + Potential extensions/Open ended
Internal Prescreen Requirements:
Purpose: The Senior Solutions Architect / Lead AI & Platform Engineer establishes the technical architecture, engineering standards, cloud foundations, and secure development practices for Massport’s software and artificial intelligence program.
This hands-on senior role converts promising concepts from Massport’s “Toy, Tool, Transform” strategy into secure, reliable, and supportable solutions. The position advises leadership on when to build, buy, configure, or integrate technology while guiding developers and directly contributing to complex software, cloud, automation, and AI initiatives.
- Someone who can build solutions and AI Frameworks, not just building the infrastructure on which the solution lives.
I. ESSENTIAL TASKS OF THE JOB:
A. Solution Architecture & Technical Strategy
- Design secure, scalable architectures for enterprise applications, AI agents, data integrations, workflow automation, and cloud or hybrid-cloud platforms.
- Define reusable standards for APIs, identity, data access, deployment, monitoring, logging, testing, resilience, and human approval workflows.
- Evaluate technical options and recommend whether Massport should build, buy, configure, integrate, modernize, or retire a solution based on security, cost, reliability, and supportability.
- Maintain architecture diagrams, data flows, technical decisions, system dependencies, and production support documentation.
B. AI, Software & Integration Engineering
- Lead and contribute to the development of applications, copilots, RAG solutions, custom AI agents, APIs, data pipelines, and automated workflows.
- Design secure integrations with Microsoft 365, including Outlook, SharePoint, OneDrive, Teams, Entra ID, Microsoft Graph, Copilot, and approved Google Cloud and Gemini for Government services.
- Use modern engineering practices and AI coding assistants to produce maintainable, tested, documented, and secure software.
- Ensure AI solutions preserve source-system permissions, provide traceability, and include appropriate evaluation, monitoring, and human oversight.
C. Cloud, Platform & Reliability Engineering
- Design and support cloud, hybrid-cloud, Linux, containerized, and on-premises environments using Azure, Google Cloud Platform, AWS, Docker, Kubernetes, and related technologies.
- Implement infrastructure-as-code, configuration management, CI/CD, automated testing, patching, secrets management, and repeatable deployment practices using tools such as Terraform, Ansible, Bash, and PowerShell.
- Establish observability, alerting, service reliability, backup, recovery, capacity, and incident-response standards for production systems.
- Lead complex troubleshooting, root-cause analysis, vulnerability remediation, and corrective engineering actions.
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